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arXiv · 2206.15075

Topological data analysis and machine learning

Daniel Leykam·Dimitris G. Angelakis
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Abstract

Topological data analysis refers to approaches for systematically and reliably computing abstract ``shapes'' of complex data sets. There are various applications of topological data analysis in life and data sciences, with growing interest among physicists. We present a concise yet (we hope) comprehensive review of applications of topological data analysis to physics and machine learning problems in physics including the detection of phase transitions. We finish with a preview of anticipated directions for future research.

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cond-mat.mes-hallphysics.opticsquant-ph

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Daniel Leykam, Dimitris G. Angelakis. 2022-06-30. Topological data analysis and machine learning. https://doi.org/10.1080/23746149.2023.2202331

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